With accumulating public omics data, great efforts have been made to characterize the genetic heterogeneity of breast cancer. However, identifying novel targets and selecting the best from the sizeable lists of candidate targets is still a key challenge for targeted therapy, largely owing to the lack of economical, efficient and systematic discovery and assessment to prioritize potential therapeutic targets. Here, we describe an approach that combines the computational evaluation and objective, multifaceted assessment to systematically identify and prioritize targets for biological validation and therapeutic exploration. We first establish the reference gene expression profiles from breast cancer cell line MCF7 upon genome-wide RNA interference (RNAi) of a total of 3689 genes, and the breast cancer query signatures using RNA-seq data generated from tissue samples of clinical breast cancer patients in the Cancer Genome Atlas (TCGA). Based on gene set enrichment analysis, we identified a set of 510 genes that when knocked down could significantly reverse the transcriptome of breast cancer state. We then perform multifaceted assessment to analyze the gene set to prioritize potential targets for gene therapy. We also propose drug repurposing opportunities and identify potentially druggable proteins that have been poorly explored with regard to the discovery of small-molecule modulators. Finally, we obtained a small list of candidate therapeutic targets for four major breast cancer subtypes, i.e., luminal A, luminal B, HER2+ and triple negative breast cancer. This RNAi transcriptome-based approach can be a helpful paradigm for relevant researches to identify and prioritize candidate targets for experimental validation.

Yersinia pestis is among the most dangerous human pathogens, and systematic research of this pathogen is important in bacterial pathogenomics research. To fully interpret the biological functions, physiological characteristics, and pathogenesis of Y. pestis, a comprehensive annotation of its entire genome is necessary. The emergence of omics-based research has brought new opportunities to better annotate the genome of this pathogen. Here, the complete genome of Y. pestis strain 91001 was reannotated using genomics and proteogenomics data. One hundred and thirty-seven unreliable coding sequences were removed, and 41 homologous genes were relocated with their translational initiation sites, while the functions of seven pseudogenes and 392 hypothetical genes were revised. Moreover, annotations of noncoding RNAs, repeat sequences, and transposable elements have also been incorporated. The reannotated results are freely available at http://tody.bmi.ac.cn.